> For the complete documentation index, see [llms.txt](https://docs.coupler.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coupler.io/sources/category/marketing/linkedin-public-data/best-practices.md). # Best Practices ## Recommended setup


Start with simple report types	Begin with "Page: lifetime overview" or "Page: cumulative posts performance" before moving to time-based reports. These don't require date ranges and are less prone to issues.
Use separate flows for different report types	Create one data flow per report type rather than trying to combine them. This makes troubleshooting easier and keeps your destination cleaner. You can combine them later using Append transformations.
Test with data preview first	Always check the data preview before running the full flow. This shows you exactly what will be exported and catches missing-data issues early.
Append historical snapshots	For time-series analysis, set your flow to append rather than replace. This builds a historical record over time so you can track trends.

## Data refresh and scheduling


Schedule daily for performance insights	"Page: performance insights" and "Page: follower gains trend" change daily. Schedule these flows to run once per day, preferably outside 9 AM–5 PM (avoid peak API usage).
Run weekly for demographic reports	Demographic data (follower/audience demographics) changes slowly. Weekly or bi-weekly runs are sufficient and reduce unnecessary API calls.
Use lifetime snapshot for reference	Run "Page: lifetime overview" once per week or month as a reference point. Changes slowly and useful for high-level health checks.

## Performance optimization


Limit date ranges for large datasets	If pulling 1+ years of post or performance data, split it into quarters using date ranges. This prevents timeouts and keeps exports manageable.
Choose one demographic dimension per flow	For demographic reports, select one breakdown dimension per flow (e.g., geography OR job title, not both). This speeds up the API call and avoids data explosion.

## Common pitfalls {% columns %} {% column %} **Do** * Test manually before scheduling * Use separate flows for different report types * Check the data preview before running * Append data to build historical records * Schedule during off-peak hours * Verify your LinkedIn permissions before troubleshooting {% endcolumn %} {% column %} **Don't** * Don't run the same flow multiple times in quick succession * Don't try to combine multiple report types in one flow * Don't ignore null values in the preview — they indicate missing data * Don't export years of post data in a single run * Don't change your LinkedIn role without re-authorizing Coupler.io * Don't assume the exported data matches LinkedIn's real-time dashboard exactly (there's always a slight lag) {% endcolumn %} {% endcolumns %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.coupler.io/sources/category/marketing/linkedin-public-data/best-practices.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.